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Salary
≈ $134k – $279k per year (Estimated)
Location
In office (Jersey City)
Seniority
Staff · 5+ years exp
Visa
H-1B filings in 12 months: 3,429 · for this role: 1,686 · green card filings: 933

Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Jul 2, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

We’re looking for a tech leader ready to take their career to new heights. Join the ranks of top talent at one of the world’s most influential companies.

As a Lead Software Engineer at JPMorganChase within the Asset Wealth Management, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances.

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems

  • Develops secure and high-quality production code, and reviews and debugs code written by others

  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience

  • Hands-on practical experience delivering system design, application development, testing, and operational stability

  • Deep expertise with Adobe Experience Manager (AEM), including component development, content architecture, templates, OSGi, Sling Models, and dispatcher configurations. Experience with AEM as a Cloud Service or AEM Managed Services.
  • Strong knowledge of Adobe’s marketing ecosystem (e.g., Marketo, Adobe Analytics, Adobe Target or Engage) and how they integrate with AEM.
  • Hands-on proficiency with modern front-end technologies: JavaScript, TypeScript, React or similar frameworks, CSS/SCSS, and responsive design.
  • Solid understanding of web security, SEO best practices, web accessibility (WCAG 2.x), and performance optimization.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.

  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

  • In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience.

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